LayerStyle: ColorOverlay V2

Documentation

• Class name: LayerStyle: ColorOverlay V2
• Category: 😺dzNodes/LayerStyle
• Output node: False

The ColorOverlay V2 node applies a color overlay to an image, allowing for the adjustment of blend mode, opacity, and color to achieve various visual effects. It supports the inversion of a mask for more complex layering and styling options.

Input types

Required

• background_image
  • Specifies the background image over which the color overlay will be applied. It is a foundational element for the overlay effect.
  • Comfy dtype: IMAGE
  • Python dtype: IMAGE
• layer_image
  • Defines the layer image to which the color overlay effect will be applied, enabling the creation of layered visual effects.
  • Comfy dtype: IMAGE
  • Python dtype: IMAGE
• invert_mask
  • Determines whether the mask applied to the layer image should be inverted, offering additional control over the overlay effect.
  • Comfy dtype: BOOLEAN
  • Python dtype: BOOLEAN
• blend_mode
  • Specifies the blending mode used for combining the color overlay with the layer image, affecting the overall visual outcome. The correct data type should reflect a custom enumeration or selection type, not a standard Python data type.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: Enum or custom type representing blend modes
• opacity
  • Controls the opacity level of the color overlay, allowing for fine-tuning of the effect's intensity.
  • Comfy dtype: INT
  • Python dtype: INT
• color
  • Sets the color of the overlay, enabling customization of the visual effect.
  • Comfy dtype: STRING
  • Python dtype: STRING

Optional

• layer_mask
  • Optional mask that can be applied to the layer image for more precise control over the overlay effect.
  • Comfy dtype: MASK
  • Python dtype: MASK

Output types

• image
  • Comfy dtype: IMAGE
  • The resulting image after applying the color overlay effect, incorporating adjustments made through the node's parameters.
  • Python dtype: IMAGE

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class ColorOverlayV2:

    def __init__(self):
        pass

    @classmethod
    def INPUT_TYPES(self):

        return {
            "required": {
                "background_image": ("IMAGE", ),  #
                "layer_image": ("IMAGE",),  #
                "invert_mask": ("BOOLEAN", {"default": True}),  # 反转mask
                "blend_mode": (chop_mode_v2,),  # 混合模式
                "opacity": ("INT", {"default": 100, "min": 0, "max": 100, "step": 1}),  # 透明度
                "color": ("STRING", {"default": "#FFBF30"}),  # 渐变开始颜色
            },
            "optional": {
                "layer_mask": ("MASK",),  #
            }
        }

    RETURN_TYPES = ("IMAGE",)
    RETURN_NAMES = ("image",)
    FUNCTION = 'color_overlay_v2'
    CATEGORY = '😺dzNodes/LayerStyle'

    def color_overlay_v2(self, background_image, layer_image,
                  invert_mask, blend_mode, opacity, color,
                  layer_mask=None
                  ):

        b_images = []
        l_images = []
        l_masks = []
        ret_images = []
        for b in background_image:
            b_images.append(torch.unsqueeze(b, 0))
        for l in layer_image:
            l_images.append(torch.unsqueeze(l, 0))
            m = tensor2pil(l)
            if m.mode == 'RGBA':
                l_masks.append(m.split()[-1])
        if layer_mask is not None:
            if layer_mask.dim() == 2:
                layer_mask = torch.unsqueeze(layer_mask, 0)
            l_masks = []
            for m in layer_mask:
                if invert_mask:
                    m = 1 - m
                l_masks.append(tensor2pil(torch.unsqueeze(m, 0)).convert('L'))
        if len(l_masks) == 0:
            log(f"Error: {NODE_NAME} skipped, because the available mask is not found.", message_type='error')
            return (background_image,)

        max_batch = max(len(b_images), len(l_images), len(l_masks))
        _color = Image.new("RGB", tensor2pil(l_images[0]).size, color=color)
        for i in range(max_batch):
            background_image = b_images[i] if i < len(b_images) else b_images[-1]
            layer_image = l_images[i] if i < len(l_images) else l_images[-1]
            _mask = l_masks[i] if i < len(l_masks) else l_masks[-1]
            # preprocess
            _canvas = tensor2pil(background_image).convert('RGB')
            _layer = tensor2pil(layer_image).convert('RGB')
            if _mask.size != _layer.size:
                _mask = Image.new('L', _layer.size, 'white')
                log(f"Warning: {NODE_NAME} mask mismatch, dropped!", message_type='warning')

            # 合成layer
            _comp = chop_image_v2(_layer, _color, blend_mode, opacity)
            _canvas.paste(_comp, mask=_mask)

            ret_images.append(pil2tensor(_canvas))

        log(f"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
        return (torch.cat(ret_images, dim=0),)